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* test(e2e): failed request error span carries the full untruncated message and status Covers logging.otel.failure.exports_metric on chat_completions: a request that fails at the provider (invalid upstream key deployment) must export one complete trace whose gen-AI span carries the LIT-4179 error contract, declared as one reviewable payload (EXPECTED_ERROR_SPAN_ATTRIBUTES) plus an untruncated error.message proven by parsing the embedded provider error JSON back out of the attribute. The root SERVER span must record the 401 the client received. Adds STORE_MODEL_IN_DB to the compose stack so /model/new works locally, which the suite's model-registering tests already assume * test(e2e): clean failure diagnostics on the error-span contract per review A truncated error.message with missing braces now fails with a readable assertion instead of an unhandled ValueError, an unparseable embedded JSON fails via pytest.fail with the truncation context, and the retry loop now asserts the upstream provider failure was actually observed so a fresh-key propagation deadline cannot masquerade as a trace-export failure * test(e2e): pin the full error attribute set including the litellm.provider.error keys The LIT-4179 fix restored error.message/code/stack_trace/llm_provider; a later refactor (#32591) moved the litellm-specific keys under litellm.provider.error.*, which the initial contract missed. The payload now pins error, error.type, otel.status_code, litellm.provider.error.code=401, and litellm.provider.error.llm_provider=anthropic exactly, plus non-empty litellm.provider.error.stack_trace and the untruncated error.message * test(e2e): author the error-span test docstring
140 lines
4.4 KiB
YAML
140 lines
4.4 KiB
YAML
# local setup to run e2e tests
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configs:
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litellm_config:
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content: |
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general_settings:
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master_key: os.environ/LITELLM_MASTER_KEY
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database_url: os.environ/DATABASE_URL
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store_prompts_in_spend_logs: true
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proxy_budget_rescheduler_min_time: 5
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proxy_budget_rescheduler_max_time: 10
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litellm_settings:
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drop_params: true
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num_retries: 3
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request_timeout: 600
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cache: true
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cache_params:
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type: redis
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host: redis
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port: 6379
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# OTEL v2 trace destination for the logging suite's trace-completeness
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# tests: the arize_phoenix preset is OTLP with a configurable endpoint
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# (PHOENIX_COLLECTOR_HTTP_ENDPOINT below points it at the jaeger service),
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# so gen-AI spans export through a preset-owned provider - the code path
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# where trace splits actually happen - with no cloud credentials needed.
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callbacks: ["arize_phoenix"]
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router_settings:
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routing_strategy: simple-shuffle
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num_retries: 3
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allowed_fails: 5
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cooldown_time: 30
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fallbacks:
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- gemini-2.5-flash: ["gpt-5.5", "claude-haiku-4-5"]
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finetune_settings:
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- custom_llm_provider: openai
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api_key: os.environ/OPENAI_API_KEY
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files_settings:
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- custom_llm_provider: openai
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api_key: os.environ/OPENAI_API_KEY
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- custom_llm_provider: azure
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api_base: os.environ/AZURE_API_BASE
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api_key: os.environ/AZURE_API_KEY
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api_version: "2024-05-01-preview"
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model_list:
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- model_name: gpt-5.5
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litellm_params:
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model: openai/gpt-5.5
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api_key: os.environ/OPENAI_API_KEY
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- model_name: claude-haiku-4-5
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litellm_params:
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model: anthropic/claude-haiku-4-5
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api_key: os.environ/ANTHROPIC_API_KEY
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- model_name: gemini-2.5-flash
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litellm_params:
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model: gemini/gemini-2.5-flash
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api_key: os.environ/GEMINI_API_KEY
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- model_name: openai-text-embedding-3-small
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litellm_params:
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model: openai/text-embedding-3-small
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api_key: os.environ/OPENAI_API_KEY
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services:
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litellm:
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image: ghcr.io/berriai/litellm:main-latest
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depends_on:
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db:
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condition: service_healthy
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redis:
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condition: service_healthy
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jaeger:
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condition: service_healthy
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env_file: .env
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environment:
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LITELLM_MASTER_KEY: sk-1234
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STORE_MODEL_IN_DB: "True"
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LITELLM_OTEL_V2: "true"
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PHOENIX_COLLECTOR_HTTP_ENDPOINT: http://jaeger:4318/v1/traces
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PHOENIX_API_KEY: local-jaeger-noauth
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DATABASE_URL: postgresql://litellm:litellm@db:5432/litellm
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UI_USERNAME: admin
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UI_PASSWORD: sk-1234
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AWS_S3_BUCKET_NAME: ${AWS_S3_BUCKET_NAME:-${AWS_BATCH_S3_BUCKET:-}}
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AWS_BATCH_S3_BUCKET: ${AWS_BATCH_S3_BUCKET:-${AWS_S3_BUCKET_NAME:-}}
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AWS_BATCH_ROLE_ARN: ${AWS_BATCH_ROLE_ARN:-}
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AWS_ACCESS_KEY_ID: ${AWS_ACCESS_KEY_ID:-}
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AWS_SECRET_ACCESS_KEY: ${AWS_SECRET_ACCESS_KEY:-}
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AWS_REGION: ${AWS_REGION:-us-east-1}
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GCS_BUCKET_NAME: ${GCS_BUCKET_NAME:-}
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VERTEXAI_PROJECT: ${VERTEXAI_PROJECT:-}
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VERTEXAI_CREDENTIALS: ${VERTEXAI_CREDENTIALS:-}
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GOOGLE_APPLICATION_CREDENTIALS: ${GOOGLE_APPLICATION_CREDENTIALS:-}
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MISTRAL_API_KEY: ${MISTRAL_API_KEY:-}
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AZURE_API_BASE: ${AZURE_API_BASE:-}
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AZURE_API_KEY: ${AZURE_API_KEY:-}
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ports:
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- "4000:4000"
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configs:
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- source: litellm_config
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target: /app/config.yaml
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command: ["--config", "/app/config.yaml", "--port", "4000"]
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# throwaway db
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db:
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image: postgres:16
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environment:
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POSTGRES_USER: litellm
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POSTGRES_PASSWORD: litellm
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POSTGRES_DB: litellm
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healthcheck:
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test: ["CMD-SHELL", "pg_isready -U litellm"]
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interval: 3s
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timeout: 3s
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retries: 20
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redis:
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image: redis:7
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healthcheck:
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test: ["CMD", "redis-cli", "ping"]
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interval: 3s
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timeout: 3s
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retries: 20
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# throwaway OTEL trace destination (OTLP ingest on 4318 inside the network,
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# query API on host 16686 for test read-back; see E2E_OTEL_QUERY_URL)
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jaeger:
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image: jaegertracing/all-in-one:1.62.0
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ports:
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- "16686:16686"
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healthcheck:
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test: ["CMD", "wget", "-qO-", "http://localhost:14269/"]
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interval: 3s
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timeout: 3s
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retries: 20
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